Real-time PCR has become the method of choice in various gene-related applications because it is conceptually straightforward, flexible and sensitive while generating quantitative data (Heid et al., 1996, Genome Res. 6:986). Its applicability as an important diagnostic tool has been demonstrated in many clinical applications (e.g., Bustin, 2002, J. Mol. Endo. 29:23). However, its inherent wide variability of results (Reinhold et al., 2001, J. Clin. Onc. 19:1723) still makes it unreliable in clinical diagnostics. The major drawback is that all known real-time PCR methods (and instruments) have not yet achieved the levels of sensitivity, fidelity, accuracy, reproducibility and resolution necessary for true absolute quantification of low abundance targets. Moreover, new reagents, chemistries and instruments continuously introduced into the real-time PCR field make it increasingly difficult to compare results obtained in different laboratories and at different times (Bustin, 2002).
Quantification of an amplified target in “real-time” PCR is based on measuring the reaction product by sampling its fluorescence in the reaction mix during the course of the amplification reaction, generally at each cycle (Heid et al., 1996). The fluorescence gives a measure of the reaction's kinetics, which allows building a kinetic curve for the reaction and assessing a linearity range for the reaction (e.g., in logarithmic scale). In order to estimate the amount of the target nucleic acid prior to amplification (e.g., the number of original copies of the target, prior to amplification), one only needs a calibration curve, which is built from a series of kinetic curves recorded for the target nucleic acid at known target dilutions. The calibration curve is then used to estimate the concentration of target in unknown samples, on the assumption that the reaction kinetics (the efficiencies of amplifying the target materials) for each calibration dilution are the same, and that they are equal to those in the experimental sample. This in turn requires the calibration curve to be linear on a logarithmic scale.
Quantification of the real-time PCR is centered on the assumption that the fluorescence recorded at each cycle represents the amount of the amplified target DNA. Fluorescence of a sample is normalized to that of an internal reference fluorophore to correct for fluctuations in volume and/or concentration and recorded as a point on a kinetic curve. The point at which the fluorescent signal is first recorded as statistically significant above the background is defined as threshold cycle (Ct). It is assumed that Ct occurs during the exponential phase of the PCR, so that quantification is not affected by biases of the plateau phase. The Ct value is reported for each sample and then made into a quantitative result, e.g., the initial target concentration or number of target copies is estimated by comparison to an external calibration (or “standard”) curve.
An inherent problem when using a calibration or standard curve is that the reaction saturates very quickly, and background fluorescence in the absence of amplification is typically very high. Early detection is precluded by high background fluorescence that occurring the absence of amplification. This is because the level of noise associated with the background is higher than the useful signal generated by the PCR product on early cycles, which makes the PCR product effectively undetectable at the beginning of the reaction. Also, for the product quantification using a calibration or standard curve, it is assumed that during the early amplification cycles the reaction efficiency (i.e., fold increase per cycle) is the same as in later cycles.
There are currently two major approaches to PCR quantification: relative and absolute. Relative quantification is used to determine the changes in nucleic acid levels (e.g., differences between samples of different kinds, or in cells that have been differently treated). For a relative calibration curve, a series of dilutions of a calibrator sample are used. The calibrator can be any nucleic acid with known concentration and amplicon length. During PCR amplification, Ct numbers for the calibrator dilutions are detected and plotted against arbitrary units. The target Ct numbers are applied directly to the calibration curve, and the result is expressed as fold increase or decrease relative to the reference measurement.
In contrast, absolute quantification seeks to determine the number of target copies initially present in a sample. It requires the building of an absolute calibration curve for each individual amplicon as a measure of the efficiencies of amplification during all amplification steps, including the reverse transcription step (e.g., when performing reverse transcription PCR, RT-PCR) and during PCR amplification. Since the standard template must be pure (i.e., a standard free from non-target RNA/DNA contamination), it is usually prepared from recombinant DNA or RNA. Serial dilutions of the DNA/RNA standard are prepared, and each dilution is re-assayed in the same PCR run along with experimental samples and positive and negative controls. Ct values for each standard dilution are recorded and a standard curve is generated by plotting the Ct values against the logarithm of the initial copy numbers, which are inversely proportional to each other. The initial target copy number (TCN) of the experimental sample is calculated using a linear regression equation of that calibration curve and Ct values for the experimental sample. Because of the sample-to-sample variations in the amount of starting material, especially in clinical samples, the results are normalized by tissue mass, cell number, or nucleic acid amount (e.g., total DNA or RNA, ribosomal RNA, or cDNA/mRNA of for example, housekeeping genes) (Bustin, 2002; Bustin, 2002, J. Mol. Endo. 25:169).
Although the objective is to identify a precise initial TCN, absolute quantification of the real-time PCR method has a principle flaw in that it is based on an external calibration. The external calibration requires ideal validation of identical reaction kinetics (i.e. amplification efficiencies) for the calibrator template and the target template (Pfaffl and Hageleit, 2001, Biotech. Lett. 23:275; Klein, 2002, Trends Mol. Med. 8:257). Such validation is extremely difficult, even for ideal samples, let alone experimental and clinical samples from different laboratories and testing sites, different tissues, animals and patients. In addition, clinical samples can vary widely in purity, making it very difficult to provide truly identical reaction conditions for both the purified control and the clinical sample.
The accuracy of the absolute quantification method depends heavily on a few critical assumptions. The first assumption is that targets and calibrators are amplified with the same efficiency. Another assumption is that the efficiencies for calibrator and target detected at Ct are identical to those in the earlier cycles. However, clinical samples often contain contaminants and/or inhibitors that reduce the efficiency of the amplification reaction compared to the pristine samples used as calibrator templates. In addition, inhibitors appear to have a stronger effect in the earlier cycles (they may degrade, e.g., by exposure to the extreme temperature of PCR, by the later cycles), which then results in underestimation of the copy number for a reaction. The exponential nature of the PCR, combined with a small number of the target molecules leads to a situation where small variations in efficiencies during the early cycles causes great variations of the final yield of the amplified product (Bustin, 2002). As a result, PCR-based quantification is often characterized by significant variations and non-reproducibility. Therefore, a large variety of enzymes, primers, and test samples, and the absence of acceptable validation and normalization procedures leads to poor reproducibility of data in different laboratories and raises serious doubts about how quantitative, reproducible or statistically informative real-time PCR is (e.g., Bustin 2002). Therefore, the usefulness and reliability of using quantitative real-time PCR as a routine clinical diagnostic is questionable (Bustin 2000, 2002; Klein 2002; Pfaffl and Hageleit, 2001).
PCR is, to date, the best method for detecting low abundance nucleic acid molecules. However, the statistics of particle distribution predicts that quantification of small numbers of molecules makes Ct data less reproducible due to stochastic effects (Rasmussen, R (2001) Quantification on the LightCycler. In: Meuer, S, Wittwer, C, Nakagawara, K, eds. Rapid Cycle Real-time PCR, Methods and Applications. Springer Press, Heidelberg; p. 21-34) which, in combination with all the other drawbacks as previously listed, makes quantification of the low abundance target even less reliable.
There exists a PCR-based method to assess directly the small numbers of DNA/RNA molecules. The approach is based on competitive end-point PCR of multiple sub-microliter samples containing two terminally diluted targets labeled with different fluorescent markers excitable at different wavelengths (e.g., a control target of known TCN and an unknown target of unknown TCN). Following PCR amplification, the samples undergo relative quantification of the two targets (e.g., either by capillary electrophoresis, Lagally et al., 2001, Anal. Chem. 73:565; Lagally et al., 2001, Lab on a Chip, 1:102, or fluorescence detection by confocal microscope, Kalinina et al., 1997, Nucl. Acids Res. 25:1999). The distribution function of the amplified product is analyzed using Poisson statistics best-fit method. Although the described approach enables a statistically significant absolute quantification of the TCN in the original sample and does not require any external calibration, it relies on the relative quantification of the control and the target components after the end-point PCR. This by itself lowers the quantification accuracy and makes the method both time and labor consuming. This approach has been utilized to demonstrate single copy. PCR amplification (Lagally et al., 2001; Kalinina et al., 1997). It has not become a routine quantitative method because, in order to collect statistics sufficient for accurate target quantification, it requires rather complicated sample handling and the detection of hundreds of separate PCR amplification reactions.
Efforts in improving quantitative PCR also include the desire to minimize the time-to-result and the cost per result. Approaches generally include decreasing the amplification reaction volume and at the same time increasing the number of reactions that are performed simultaneously (e.g., by use of high throughput systems). The microchamber army for PCR amplification described by Nagai et al. (2001, Biosens. Bioelec. 16:1015) demonstrated that high-throughput, rapid, synchronous amplification of multiple amplification targets was possible. The PicoTiterPlate™ as described by Leamon et al., 2003, Electophoresis 24:3769, further demonstrated that amplification using low reaction volumes (as low as 39.5 μl) and low starting template copy number (calculated as 5 copies of template per reaction) in a high throughput format (up to 300,000 discrete reactions on one plate) was possible. Leamon goes one step further and describes his method as being a method for quantitative PCR. However, the quantitative PCR of Leamon is a relative and not absolute quantification, in that a standard curve was generated and fluorescence readings were applied to the curve to define amplicon fold increase in an end-point PCR assay.
The BioMark™ system developed by Fluidigm Corporation (San Francisco, Calif.) advertises a nanofluidic chip reported to absolutely quantify target nucleic acids (Application Marketing Note MRKT00047.VD). The literature describes constant amplification monitoring via fluorescence detection, such that the system is a real-time PCR system. However, when calculations are performed on the data as described, mathematical analysis does not bear out the conclusions, i.e., absolute quantification of the sample template was not, in fact, realized. The results as listed do not satisfy a Poisson distribution curve (i.e., bell-shaped curve). For example, when taking the white counts found in FIG. 2, 5 pg DNA slide (count=310) and applying the Poisson probability equation, the λ parameter (i.e., a shape parameter that indicates the average number of events in a given time period) is calculated to be λ=0.25, indicating that the white compartment counts found in FIG. 2 should be around 273, which differs from the reported results by two standard deviations-outside the range of random probability. When calculating the λ parameter of the 1 pg DNA slide (count-62), λ=0.50. Therefore, the disparity in the average number of events in a given time period and data reported that is actually outside the range of random probability demonstrates that, under the experimental conditions reported, absolute quantification of target nucleic acids has not occurred.
As such, the lack of automated, reliable, absolute quantification in nucleic acid amplification methods is a huge obstacle for introducing these methods in clinical diagnostics where the problems are multiplied by, for example, variations in samples from different patients, sample collection conditions, and technical loading errors. This variation makes it practically impossible to relate the results from, for example, different laboratories, methods, patients and tissues in terms of target copy number. Consequently, it is impossible to establish databases originating from PCR results obtained in various studies and proves to be a critical impediment for utilizing real time PCR as a clinical tool.
Therefore, what are needed are new methods and devices that provide approaches for high-throughput, highly accurate nucleic acid quantification such that direct, absolute quantification of target amplicons is realized. Such methods and devices will not only aide in bringing continuity and consistency to clinical diagnostics, but also serve as improved research tools for the scientific community as they perform the needed research to decipher the genes and related sequences that impact daily lives.